- They are twice as likely to redesign workflows to incorporate AI rather than simply adding AI tools.
- They are three times (2.8x) more likely to have increased the number of decisions made without human intervention, while also going further on AI governance.
A small group of companies is pulling sharply ahead in the race to generate real financial returns from artificial intelligence, according to PwC's new AI Performance study.
The global study interviewed 1,217 senior executives, primarily at large, publicly listed companies across 25 sectors, asking them about the revenue and efficiency gains they are seeing from AI today, alongside questions about how they deploy the technology.
It finds that nearly three?quarters (74%) of AI's economic value is captured by just one?fifth (20%) of organisations, revealing a stark and widening divide between a small group of AI leaders and the majority of businesses still stuck in pilot mode.
The research shows that these top?performing companies are not simply deploying more AI tools. Instead, they are using AI as a catalyst for growth and business reinvention, particularly by pursuing new revenue opportunities created as industries converge, while building strong foundations around data, governance and trust.
Joe Atkinson, Global Chief AI Officer, PwC, said:
"Many companies are busy rolling out AI pilots, but only a minority are converting that activity into measurable financial returns. The leaders stand out because they point AI at growth, not just cost reduction, and back that ambition with the foundations that make AI scalable and reliable."
Growth, not just productivity, separates AI leaders
Organisations with the strongest AI performance treat the technology as a reinvention engine, using it to reshape business models and expand beyond traditional industry boundaries. Companies leading on AI report:
- 2.6 times as likely as peers to report AI improves their ability to reinvent their business model;
- Two to three times as likely as others to say they use AI to identify and pursue growth opportunities arising from industry convergence, such as collaborating with partners outside their core sector.
PwC's analysis shows that capturing growth opportunities from industry convergence is the single strongest factor influencing AI?driven financial performance, ahead of efficiency gains alone.
Trust and automation combine to delivering outcomes
The research also highlights significant differences in how leading companies deploy AI inside the enterprise. Companies with the best AI-driven financial outcomes are nearly twice as likely as other companies to say they're using AI in advanced ways: executing multiple tasks within guardrails (1.8x) or operating in autonomous, self-optimising ways (1.9x).
AI leaders are increasing the number of decisions made without human intervention at almost three times (2.8x) the rate of peers.
This automation is enabled by a focus on 'trust at scale'. AI leaders are more likely than other companies to have mechanisms such as a Responsible AI framework (1.7x as likely as other companies) and a cross-functional AI governance board (1.5x). As a result of their efforts, their employees are twice as likely to trust AI outputs.
A widening gap
Without a shift in approach, the performance gap between AI leaders and laggards is likely to widen further as leading companies continue to learn faster, scale proven use cases and automate decisions safely at scale.
Pisit Thangtanagul, CEO of PwC Thailand, added:
"Across Asia, we're seeing organisations increasingly move beyond experimentation and scale AI across the enterprise to deliver measurable outcomes in both revenue growth and efficiency. In Thailand, organisations are accelerating investment in data, technology and AI platforms, supported by stronger governance and sharper performance metrics—so AI programmes can scale with confidence and translate into tangible business value.
"The findings reinforce a simple message: AI must be treated as a strategic growth agenda, not just a productivity tool. That starts with prioritising use cases tied directly to business outcomes—revenue, customer experience and new business models—and setting clear KPIs to track impact. To scale AI sustainably, organisations need the right data foundations, skills and trust, so AI can be deployed securely, reliably and repeatably—and become a long-term driver of competitive advantage."